This study systematically analyzed the global research landscape, technological composition, and core patents in the field of networks target and network pharmacology, and proposes further suggestions based on the IncoPat patent citation database and VOSviewer bibliometric network visualization tool. Using patent literature metrics and scientific knowledge mapping method, technological innovation pathways, research hotspots, and future directions in this field were further revealed. In particular, this field is moving towards data-driven, intelligent, and systematic approaches. Patent analysis indicated that most patent applications in this domain focused on traditional Chinese medicine(TCM), which have provided key engineering technical approaches to explore and solve complex problems of TCM. By integrating big data and artificial intelligence technologies, network targets and network pharmacology have conferred high-precision screening and quality control of key components and targets in herbal formulations and prescriptions, accelerating the clinical translation and industrialization of TCM-based new drugs and health products with medicine-food homology. Therefore, it is essential to optimize the patent protection system and establish integrated technology platforms in this field for ensuring the competitiveness of technological achievements in research and clinical application. These efforts will advance the widespread application and high-quality development of TCM modernization, precision medicine, and innovative drug discovery.
Bibliometrics ; Patents as Topic ; Humans ; Medicine, Chinese Traditional ; Network Pharmacology/trends* ; Drugs, Chinese Herbal/pharmacology*

Since the promulgation of the first Drug Administration Law of the People's Republic of China 40 years ago in 1984, China has undergone four main stages in the traditional Chinese medicine(TCM) regulation: the initial establishment of TCM regulation rules(1984-1997), the formation of a modern TCM regulatory system(1998-2014), the reform of the review and approval system for new TCM drugs(2015-2018), and the construction of a scientific regulation system for TCM(2019-2024). Over the past five years, a series of milestone achievements of TCM regulation in China have been achieved in the six aspects, including its strategic objectives and the establishment of a science-based regulatory system, the reform of the review and approval system for new TCM drugs, the optimization and improvement of the TCM standard system and its formation mechanism, comprehensive enhancement of regulatory capabilities for TCM safety, international harmonization of TCM regulation and its role in promoting innovation. Looking ahead, centered on advancing TCMRS to establish a sound regulatory framework tailored to the unique characteristics of TCM, TCM regulation will evolve into new reform patterns, advancing and extending across eight critical fronts, including the legal framework and policy architecture, the review and approval system for new TCM drugs, the quality standard and management system of TCM, the comprehensive quality & safety regulation and traceability system, the research and transformation system for TCMRS, AI-driven innovations in TCM regulation, the coordination between high-quality industrial development and high-level regulation, and the leadership in international cooperation and regulatory harmonization. In this way, a unique path for the development of modern TCM regulation with Chinese characteristics will be pioneered.
Humans ; China ; Drugs, Chinese Herbal/standards* ; History, 20th Century ; History, 21st Century ; Medicine, Chinese Traditional/trends*

The guidelines for clinical research on new drugs provide unified standards for drug developers, researchers, and regulatory authorities, playing a crucial role in new drug development. This article systematically reviews the evolution of guidelines for clinical research on new traditional Chinese medicine(TCM) drugs in China, with a focus on analyzing the current status of these guidelines and the problems that exist. It also provides interpretations of three important guidelines. The article points out that with the continuous emergence of new clinical trial design methods, development concepts, and tools, and under the background of the "three combinations" evidence evaluation system for new TCM drugs, it is imperative to revise existing guidelines, formulate new ones, and develop new tools for clinical efficacy evaluation. It is hoped that relevant departments will adopt an open attitude and work together to build a technical system of clinical research guidelines for new TCM drugs that aligns with the characteristics of TCM.
Humans ; Biomedical Research/trends* ; China ; Clinical Trials as Topic ; Drugs, Chinese Herbal/therapeutic use* ; Guidelines as Topic ; Medicine, Chinese Traditional/standards*

Small animal multimodal biomedical imaging refers to the integration of multiple imaging techniques within the same system or device to acquire comprehensive physiological and pathological information of small animals, such as mice and rats. With the continuous advancement of biomedical research, this cutting-edge technology has attracted extensive attention. Multimodal imaging techniques, based on diverse imaging principles, overcome the limitations of single-modal imaging through information fusion, significantly enhancing the overall system's sensitivity, temporal/spatial resolution, and quantitative accuracy. In the future, the integration of new materials and artificial intelligence will further boost its sensitivity and resolution. Through interdisciplinary innovation, this technology is expected to become the core technology of personalized medicine and expand its applications to drug development, environmental monitoring, and other fields, thus reshaping the landscape of biomedical research and clinical practice. This review summarized the progress on the application and investigation of multimodal biomedical imaging techniques, and discussed its development in the future.
Animals ; Multimodal Imaging/trends* ; Rats ; Mice ; Artificial Intelligence ; Diagnostic Imaging/methods* ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed

OBJECTIVE: To analyze the current status and temporal trends of the disease burden of spinal fractures in China from 1990 to 2021 based on data from the Global Burden of Disease Study 2021 (GBD 2021), aiming to provide evidence for developing prevention and treatment strategies. METHODS: Epidemiological data on spinal fractures in China, the United States of America (USA), and globally were extracted from the GBD 2021 database. Joinpoint regression models were applied to analyze temporal trends. Age-standardized incidence, prevalence, and disability-adjusted life years (DALYs) rates were calculated, with comparisons of gender- and age-group disparities. RESULTS: In 2021, the number of incident cases, prevalent cases, and DALYs of spinal fractures in China increased by 52.28%, 113.68%, and 106.98%, respectively, compared to 1990. The age-standardized incidence, prevalence, and DALYs rates rose by 11.80%, 16.11%, and 14.79%, respectively. The disease burden escalated significantly with age, peaking in individuals aged ≥75 years. Males exhibited higher age-standardized incidence and DALYs rates than females. Comparative analysis revealed that the age-standardized DALYs rate in China (4.19/100 000) was lower than that in globally (6.62/100 000) and USA (15.92/100 000). However, China showed an upward trend [annual average percentage change (AAPC)=0.19%], contrasting with a declining trend in the USA (AAPC=-0.08%). CONCLUSION The escalating disease burden of spinal fractures in China is closely linked to population aging, gender disparities, and insufficient targeted prevention policies. Future strategies should integrate age- and gender-specific interventions, including strengthened osteoporosis prevention, trauma risk control, and big data-driven precision measures, to mitigate this burden.
Humans ; China/epidemiology* ; Global Burden of Disease/trends* ; Male ; Female ; Spinal Fractures/epidemiology* ; Middle Aged ; Aged ; Disability-Adjusted Life Years ; Prevalence ; Incidence ; Adult ; Young Adult ; Adolescent ; Aged, 80 and over ; United States/epidemiology* ; Cost of Illness ; Quality-Adjusted Life Years ; Child

OBJECTIVE: To analyze the disease burden of pelvic fractures at the global, regional, and national levels from 1990 to 2023 using data from the 2023 Global Burden of Disease Study (GBD), and to predict the disease burden through 2050. METHODS: Leveraging data from the GBD 2023, this study investigated the disease burden of pelvic fractures across 204 countries and regions. Assessment indicators included incidence rate, prevalence rate, and years lived with disability (YLDs). The Joinpoint regression model was employed to analyze trends in pelvic fracture burden from 1990 to 2023, while the average annual percentage change (AAPC) was used to quantify this temporal trend. The relationship between the socio-demographic index and pelvic fracture burden was evaluated. Furthermore, the long short-term memory (LSTM) model was applied to predict trends in pelvic fracture burden through 2050. RESULTS: In 2023, the estimated number of new pelvic fracture cases globally was 7 479 884 [95% uncertainty interval ( UI): 5 293 401-10 611 876], representing a 42.74% increase from 1990. In the same year, the number of prevalent pelvic fracture cases and YLDs were 23 007 508 (95% UI: 21 021 518-25 327 165) and 3 909 228 person-years (95% UI: 2 725 498-5 194 385), respectively. Additionally, age-standardized rates exhibited an opposing downward trend. Significant disparities in the disease burden of pelvic fractures were identified across different age groups, genders, and social contexts. According to predictions from the LSTM model, the global age-standardized incidence rate (ASIR) of pelvic fractures will be approximately 88.44 per 100 000 persons by 2050, while the total number of incident cases will rise to 8 547 095. CONCLUSION Although the overall incidence rate, prevalence rate, and YLDs of pelvic fractures have exhibited an upward trend over the past three decades, the ASIR, age-standardized prevalence rate (ASPR), and age-standardized years of life lost rate (ASYR) have shown a downward trend. It is predicted that over the upcoming 26-year period, the age-standardized rate of disease burden due to pelvic fractures will further decrease, while the number of incident cases and prevalent cases will continue to exhibit an upward trend. Formulating more targeted disease prevention strategies is critical to addressing disparities across genders, regions, and other dimensions, and to mitigating the burden of pelvic fractures.
Humans ; Fractures, Bone/epidemiology* ; Pelvic Bones/injuries* ; Male ; Female ; Middle Aged ; Adult ; Incidence ; Prevalence ; Aged ; Global Burden of Disease/trends* ; Global Health ; Adolescent ; Cost of Illness ; Young Adult ; Forecasting ; Disability-Adjusted Life Years ; Memory, Short-Term

BACKGROUND: Lung cancer ranks as the foremost cause of cancer-related deaths in China, significantly undermining population health and longevity. By analyzing the trends of death and years of life lost caused by lung cancer in Handan from 2017 to 2023, data support is provided for the formulation of prevention and treatment strategies. METHODS: Lung cancer death data in Handan during 2017-2023 were collected. Excel 2010, SPSS 26.0 and Joinpoint 4.9.0.0 were used to analyze the mortality rate of lung cancer, average annual percentage change (AAPC), cause eliminated life expectancy (CELE), potential gains in life expectancy (PGLEs), Fulfillment index, potential years of life lost (PYLL), potential years of life lost rate (PYLLR), and standardized potential years of life lost rate (SPYLLR). RESULTS: The standardized mortality rate of lung cancer in Handan from 2017 to 2023 showed a decreasing trend (AAPC=-7.10%, P<0.01). The CELE of lung cancer increased by 2.49 years (AAPC=0.48%, P<0.05). The life loss rate decreased by 21.43% (AAPC=-4.61%, P<0.05). The Fulfillment index by lung cancer increased with the growth of age from 2017 to 2023. The PYLL, PYLLR, standardized potential years of life lost (SPYLL) and SPYLLR of lung cancer during 2017 to 2023 were 134,219.75 person years, 2.03‰, 98,735.63 person years, and 1.49‰, respectively. The annual PYLLR and SPYLLR showed a decreasing trend (AAPC=-6.34%, -9.34%, respectively, P<0.01). CONCLUSIONS The standardized mortality rate of lung cancer in Handan from 2017 to 2023 showed a decreasing trend, and the impact of lung cancer on life expectancy decreased. The mortality rates of lung cancer showed significant differences among different ages and genders. It is necessary to take good measures to prevent and control lung cancer in males and higher age groups.
Lung Neoplasms/mortality* ; Humans ; Male ; Life Expectancy/trends* ; Female ; China/epidemiology* ; Aged ; Middle Aged ; Aged, 80 and over ; Adult ; Young Adult

BACKGROUND: Neglected tropical diseases (NTDs) and malaria pose a major health challenge, especially in low- and middle-income countries. METHODS: Initially, we performed a descriptive analysis of the Global Burden of Disease (GBD) 2021 database, categorizing data by subtypes. Next, linear regression models were employed to analyze temporal trends. We then utilized four predictive models to forecast the future burden. Additionally, we explored the relationship between estimated annual percentage change (EAPCs) and age-standardized rates (ASRs), as well as Human Development Index (HDI) scores for 2021. Furthermore, decomposition analysis was applied to assess the influence of aging, population dynamics, and epidemiological changes. Lastly, frontier analysis was conducted to examine the connection between disease burden and sociodemographic development. RESULTS: In 2021, NTDs and malaria contributed significantly to the global disease burden, with considerable disparities across genders, age groups, Socio-demographic Index (SDI) regions, GBD regions, and individual countries. From 1990 to 2021, both the number of cases and the associated ASRs have shown a recent downward trend. The EAPCs are positively correlated with ASRs and HDI scores. Projections indicate a continued decline in disease burden through 2046. Additionally, our decomposition analysis highlighted the positive impact of aging and epidemiological shifts on the reduction of the disease burden. Finally, frontier analysis revealed that countries and regions with higher SDI scores have greater potential for further reducing their health burden. CONCLUSION While the global burden of NTDs and malaria has improved overall, significant disparities remain across regions and countries. Our findings highlight the importance of implementing targeted intervention strategies and maintaining sustained investments to tackle the ongoing challenges.
Malaria/epidemiology* ; Humans ; Neglected Diseases/epidemiology* ; Global Burden of Disease/trends* ; Global Health/statistics & numerical data* ; Male ; Female ; Tropical Medicine ; Adult ; Cost of Illness ; Child, Preschool ; Middle Aged ; Adolescent ; Young Adult ; Infant

In recent years, China has continued to face a high prevalence of oral diseases, along with uneven access to high-quality dental care. Against this backdrop, artificial intelligence (AI), as a data-driven, algorithm-supported, and model-centered technology system, has rapidly expanded its role in transforming the landscape of stomatology. This review summarizes recent advances in the application of AI in stomatology across clinical care, biomedical and materials research, education, and hospital management. In clinical settings, AI has improved diagnostic accuracy, streamlined treatment planning, and enhanced surgical precision and efficiency. In research, machine learning has accelerated the identification of disease biomarkers, deepened insights into the oral microbiome, and supported the development of novel biomaterials. In education, AI has enabled the construction of knowledge graphs, facilitated personalized learning, and powered simulation-based training, driving innovation in teaching methodologies. Meanwhile, in hospital operations, intelligent agents based on large language models (LLMs) have been widely deployed for intelligent triage, structured pre-consultations, automated clinical documentation, and quality control, contributing to more standardized and efficient healthcare delivery. Building on these foundations, a multi-agent collaborative framework centered around an AI assistant for stomatology is gradually emerging, integrating task-specific agents for imaging, treatment planning, surgical navigation, follow-up prediction, patient communication, and administrative coordination. Through shared interfaces and unified knowledge systems, these agents support seamless human-AI collaboration across the full continuum of care. Despite these achievements, the broader deployment of AI still faces challenges including data privacy, model robustness, cross-institution generalization, and interpretability. Addressing these issues will require the development of federated learning frameworks, multi-center validation, causal reasoning approaches, and strong ethical governance. With these foundations in place, AI is poised to move from a supportive tool to a trusted partner in advancing accessible, efficient, and high-quality stomatology services in China.
Artificial Intelligence ; Humans ; Oral Medicine/trends* ; China ; Delivery of Health Care ; Machine Learning

OBJECTIVES: Rheumatoid arthritis (RA) imposes a heavy burden on individuals, families, and society. This study analyzed the incidence and mortality trends of RA in China from 1990 to 2023 to provide epidemiological evidence for precise prevention and control. METHODS: Data on RA incidence, age-standardized incidence rate (ASIR), deaths, and age-standardized mortality rate (ASMR) in China by sex and age group from 1900 to 2021 were extracted from the Global Burden of Disease (GBD) 2021 database. Joinpoint regression was used to analyze trends in ASIR and ASMR. An age-period-cohort model was constructed using R4.3.1 to evaluate longitudinal age trends and estimate relative risk (RR) values for period and cohort effects. RESULTS: In 2021, the number of RA cases, ASIR, deaths, and ASMR in China were 247 300, 13.70 per 100 000, 10 300, and 0.54 per 100 000, respectively. From 1990 to 2021, the ASIR of RA increased annually among both females and males, with average annual percentage changes (AAPCs) of 0.44% and 0.72%, respectively. Over the same period, ASMR declined in the total population and among females, with AAPCs of -0.78% and -1.19%, while the change in males was not statistically significant. Age-period-cohort analysis showed that the peak incidence occurred in women aged 60-64 years and men aged 75-79 years, and mortality increased with age. The period effect for incidence rose in both sexes, reaching 1.10 [95% confidence interval (CI) 0.94 to 1.27] for females and 1.14 (95% CI 1.02 to 1.27) for males during 2017 to 2021, compared with 2002 to 2006. The mortality period effect RR exhibited a downward-upward-downward pattern, decreasing to 0.56 (95% CI 0.52 to 0.61) in females and 0.75 (95% CI 0.68 to 0.82) in males in 2017 to 2021. Cohort analysis indicated that the highest incidence risk occurred in individuals born during 2012 to 2016, while the cohort effect RR for female RA mortality showed a continuous decline beginning with the 1922 to 1926 birth cohort. CONCLUSIONS The incidence and mortality risks of RA in China have continued to decline. However, with the aging of the population, the incidence and mortality risks among the elderly have increased. Middle-aged women and elderly men should receive focused attention. Health authorities should strengthen education, prevention, and screening among middle-aged women and enhance disease monitoring in elderly populations to reduce the national burden of RA.
Humans ; China/epidemiology* ; Arthritis, Rheumatoid/epidemiology* ; Incidence ; Male ; Female ; Middle Aged ; Adult ; Aged ; Cohort Studies ; Mortality/trends* ; Age Distribution ; Age Factors ; Aged, 80 and over ; Adolescent